A DNA barcoding approach to identify plant species in multiflower honey

Phytochemical profiling of red raspberry (Rubus idaeus L.) honey and investigation of compounds related to its pollen occurrence

BACKGROUND

Red raspberry (Rubus idaeus L.) is an important nectar source for honey production in some specific habitats as well as an important crop, so the definition of the features of this kind of honey is noteworthy. However, due to its rarity on the market, red raspberry honey is poorly characterized. The aim of this work was the phytochemical characterization of honey containing red raspberry from different geographical origins, through melissopalynological analyses concurrently with untargeted metabolomics achieved with different chromatographic techniques coupled to mass spectrometry: solid-phase micro-extraction/gas chromatography/mass spectrometry (SPME-GC-MS) and high-performance liquid chromatography/Orbitrap mass spectrometry (HPLC-Orbitrap).

RESULTS

Only 4 out of the 12 samples involved in the study contained raspberry pollen as dominant pollen, although these honeys did not group in the hierarchical cluster analysis nor in the classical multidimensional scaling analyses used for data evaluation. The first result was the detection of mislabelling in two samples, which contained raspberry pollen only as minor or important minor pollen. Of the 188 compounds identified by HPLC-Orbitrap and of the 260 identified by SPME-GC-MS, 87 and 31 compounds were present in all samples, respectively. The structurally related compounds nicotinaldehyde and nicotinamide, nicotinic acid and nicotinyl alcohol were present in 100% of the samples and correlated with R. idaeus pollen count (r > 0.60, Pearson's correlation analysis).

CONCLUSION

This study reveals important aspects about the characterization of red raspberry honey and could give new insights on bee diet and preferences, since niacin compounds resulted interestingly to be related to the presence of red raspberry pollen. © 2024 Society of Chemical Industry.

Accuracy and stability enhanced honey authenticity visual tracing method via false positive-eradicating PCR assisted nucleic acid-capturing lateral flow strip

Honey authenticity guarantee is crucial for consumer health and fair-trading commerce. New visual false-positive-free molecular lateral flow strip (LFS), termed 5'-3' exonuclease activity -directed false positive-eradicating PCR assisted lateral flow strip (FPE-PCR-LFS) was developed. This FPE-PCR-LFS explored the availability of using a signal-probe as the mediator to integrate the efficient amplification module with visual LFS module. With the genomic DNA extracted from target honey, the designed signal probe would be hydrolyzed and exhausted by the 5'-3' exonuclease activity of Taq DNA polymerase in the amplification process. The hydrolyzed signal probe would not be recognized and capture on the T line with only C line of LFS, reflecting the authenticity of the tested honey. And as low as 0.5% authenticity can be accurately identified in commercial honey samples. Significantly, the false-positive-interference was successfully eradicated for the final visual results judgement, which would greatly widen the application of molecular PCR-LFS in various fields.

Stepping towards pollen DNA metabarcoding: A breakthrough in forensic sciences

This review is engaged in determining the capability of plant pollen as a significant source of evidence for the linkage between suspects and crime location in forensic sciences. Research and review articles were collected from Google Scholar, the Web of Science, and PubMed. Articles were searched using specific keywords such as "Forensic Palynology," "Pollen metabarcoding," "Plant forensics," and "Pollen" AND "criminal investigation." Boolean logic was also utilized to narrow the articles to be included in this review article. Through the literature and exploratory research, it has been observed in the current study that with advancements in technology, forensic palynology has found its application in creating an association between the crime scene and suspected individuals to have a link to it, as pollen DNA is a long-lasting investigative tool that can effectively help forensic investigations. Moreover, the literature shows that the DNA of pollen and spores has helped forensic scientists link suspects to crime scenes, and the introduction of pollen DNA metabarcoding tools has eased the efforts of palynologists to analyze pollen DNA. The introduction of DNA metabarcoding techniques to analyze pollen from plants has helped identify the geological locations of the plants and ultimately identify the culprit.

A comprehensive review of the current trends and recent advancements on the authenticity of honey

The authenticity of honey currently poses challenges to food quality control, thus requiring continuous modernization and improvement of related analytical methodologies. This review provides a comprehensively overview of honey authenticity challenges and related analytical methods. Firstly, direct and indirect methods of honey adulteration were described in detail, commenting the existing challenges in current detection methods and market supervision approaches. As an important part, the integrated metabolomic workflow involving sample processing procedures, instrumental analysis techniques, and chemometric tools in honey authenticity studies were discussed, with a focus on their advantages, disadvantages, and scopes. Among them, various improved microscale extraction methods, combined with hyphenated instrumental analysis techniques and chemometric data processing tools, have broad application potential in honey authenticity research. The future of honey authenticity determination will involve the use of simplified and portable methods, which will enable on-site rapid detection and transfer detection technologies from the laboratory to the industry.

Assessment of residual plant DNA in bulk milk for Grana Padano PDO production by a metabarcoding approach

The aim of this study was to evaluate the ability of DNA metabarcoding, by rbcl as barcode marker, to identify and classify the small traces of plant DNA isolated from raw milk used to produce Grana Padano (GP) cheese. GP is one of the most popular Italian PDO (Protected Designation of Origin) produced in Italy in accordance with the GP PDO specification rules that define which forage can be used for feeding cows. A total of 42 GP bulk tank milk samples were collected from 14 dairies located in the Grana Padano production area. For the taxonomic classification, a local database with the rbcL sequences available in NCBI on September 2020/March 2021 for the Italian flora was generated. A total of 8,399,591 reads were produced with an average of 204,868 per sample (range 37,002-408,724) resulting in 16, 31 and 28 dominant OTUs at family, genus and species level, respectively. The taxonomic analysis of plant species in milk samples identified 7 families, 14 genera and 14 species, the statistical analysis conducted using alpha and beta diversity approaches, did not highlight differences among the investigated samples. However, the milk samples are featured by a high plant variability and the lack of differences at multiple taxonomic levels could be due to the standardisation of the feed rationing, as requested by the GP rules. The results suggest that DNA metabarcoding is a valuable resource to explore plant DNA traces in a complex matrix such as milk.

Authentication of incense (Pittosporum undulatum Vent.) honey from the Azores (Mel dos Açores) by a novel real-time PCR approach

'Mel dos Açores' is a unique nectar honey produced from the exceptional and diverse flora of the Azores archipelago, categorised as incense honey ('mel de incenso') or multifloral honey ('mel multiflora'). Incense honey should contain over 30 % of pollen grains of Pittosporum undulatum Vent. In this work, a real-time PCR method targeting the ITS region was proposed for the first time to detect P. undulatum in the honey from the Azores. The approach exhibited high analytical performance, achieving a quantification limit of 0.01 pg of incense DNA. The method was successfully applied to 22 honey samples, from which incense was detected in all 9 monofloral incense honeys and in 5 out of 10 multifloral samples from the Azores. Generally, the quantitative results for incense DNA were in good agreement with the melissopalynological data. Therefore, a simple, cost-effective and reliable tool was herein proposed to authenticate and valorise the Azores honey.

Honey Quality Control: Review of Methodologies for Determining Entomological Origin

Honey is a widely consumed natural product, and its entomological origin can significantly influence its market value. Therefore, traceability of the entomological origin of honey should also be considered in honey quality control protocols. Although several methods exist, such as physicochemical characterization and bioactivity profiling of honey of different entomological origins, the most promising three methods for entomological authentication of honey include protein-based identification, chemical profiling, and a DNA-based method. All of these methods can be applied for reliable identification of the entomological origin of honey. However, as the honey is a complex matrix, the inconsistency of the results obtained by these methods is a pragmatic challenge, and therefore, the use of each method in all the cases is questionable. Most of these methodologies can be used for authentication of newly harvested honey and it is worth understanding the possibility of using these methods for authentication of relatively old samples. Most probably, using DNA-based methods targeting small fragments of DNA can provide the best result in old samples, however, the species-specific primers targeting short fragments are limited and not available for all species. Therefore, using universal primers in combination with a DNA metabarcoding approach can be a good solution that requires further investigation. This present article describes the applications of different methods, their pros, and their cons to identify honey based on entomological origin.

Towards DNA-Based Methods Analysis for Honey: An Update

Honey is a natural product widely consumed all over the world due to its relationship with healthy benefits. Additionally, environmental and ethical issues have a higher weight in the consumer's choice to buy honey as a natural product. Following the high demand of this product, several approaches have been suggested and developed aiming at the assessment of honey's quality and authenticity. Target approaches, such as pollen analysis, phenolic compounds, sugars, volatile compounds, organic acids, proteins, amino acids, minerals, and trace elements, showed an efficacy, particularly concerning the honey origin. However, a special highlight is given to DNA markers, due to their useful applicability in environmental and biodiversity studies, besides the geographical, botanical, and entomological origins. Different DNA target genes were already explored for addressing diverse sources of honey DNA, with DNA metabarcoding attaining a relevant importance. This review aims to describe the latest advances on DNA-based methods applied in honey related studies, identifying the research needs for the development of new and additional required methodologies, and to select the most adequate tools for future research projects.

Metabarcoding of eDNA for tracking the floral and geographical origins of bee honey

Authentic honey products have a high commercial value and are often falsified via adulteration. Metabarcoding of environmental DNA (eDNA) from bacterial, floral, and entomological sources has recently been proposed as a useful tool for identifying and authenticating floral and geographical origins of bee honey. In this study, eDNA metabarcoding was applied to reveal the bacterial, plant, and honey bee DNA signatures of 48 commercial honey products from six different geographical origins. Bacterial DNA composition in commercial honey showed different relative abundance of Paenibacillus and Bacillus in geographically different samples, and high abundance of Methylobacterium in chestnut honey implying potential use of bacterial DNA composition for honey authentication. Using the chloroplast trnL (UAA) as a DNA marker, floral origins of commercial honey were investigated. Based on floral DNA signatures, 12 monofloral honey samples were identified among the 45 samples tested. Targeted amplicon sequencing of cytochrome oxidase I (COI) gene from entomological DNA identified three different Apis mellifera sequence variants, specific to geographic origin of honey, suggesting that COI can be implemented as a DNA marker to trace the origin of honey. Therefore, the current study demonstrated the potential of eDNA based metabarcoding as a robust tool for evaluating commercial bee honey by exploring their floral and geographical origins.

Accurate and Rapid Genetic Tracing the Authenticity of Floral Originated Honey with the Molecular Lateral Flow Strip

Honey is a natural product and is heavily consumed for its well-known nutritional functions. Honeys with different floral origins possess distinctive flavors, tastes, functions and economic values. It is vital to establish an effective strategy for identifying the authenticity of honey. The intrinsic genetic materials of pollen were adopted as target analytes for the effective identification of honey with floral origins. With an optimized protocol for the rapid gene extraction from honey, target genetic templates were amplified on-site with a portable device. Conveniently, all on-site amplified functional products were easily judged by the designed lateral flow strip (LFS), which was defined as the molecular LFS in this research. Additionally, the entire on-site genetic authentication of honey was completed in less than 2 h by visual observation. Commercial honey products have been successfully identified with excellent accuracy. This low-cost, high-efficiency and easy-operational strategy will greatly benefit the quality guarantee of foods with specific functions and geographical markers.

Reconstructing the ecosystem context of a species: Honey-borne DNA reveals the roles of the honeybee

To assess a species’ impact on its environment–and the environment’s impact upon a species–we need to pinpoint its links to surrounding taxa. The honeybee (Apis mellifera) provides a promising model system for such an exercise. While pollination is an important ecosystem service, recent studies suggest that honeybees can also provide disservices. Developing a comprehensive understanding of the full suite of services and disservices that honeybees provide is a key priority for such a ubiquitous species. In this perspective paper, we propose that the DNA contents of honey can be used to establish the honeybee’s functional niche, as reflected by ecosystem services and disservices. Drawing upon previously published genomic data, we analysed the DNA found within 43 honey samples from Northern Europe. Based on metagenomic analysis, we find that the taxonomic composition of DNA is dominated by a low pathogenicity bee virus with 40.2% of the reads, followed by bacteria (16.7%), plants (9.4%) and only 1.1% from fungi. In terms of ecological roles of taxa associated with the bees or taxa in their environment, bee gut microbes dominate the honey DNA, with plants as the second most abundant group. A range of pathogens associated with plants, bees and other animals occur frequently, but with lower relative read abundance, across the samples. The associations found here reflect a versatile the honeybee’s role in the North-European ecosystem. Feeding on nectar and pollen, the honeybee interacts with plants–in particular with cultivated crops. In doing so, the honeybee appears to disperse common pathogens of plants, pollinators and other animals, but also microbes potentially protective of these pathogens. Thus, honey-borne DNA helps us define the honeybee’s functional niche, offering directions to expound the benefits and drawbacks of the associations to the honeybee itself and its interacting organisms.

Identification of Seasonal Honey Based on Quantitative Detection of Typical Pollen DNA

Monofloral honey is produced from the nectar of a single predominant botanical species in a particular season and has certain unique properties. Valuable monofloral honey produced in a particular season with unique properties is often targeted for adulteration. Herein, a method for the identification of monofloral honey and determination of its production season was developed. Major nectar plants, including Prunus sp., Robinia pseudoacacia, Castanea sp., and Kalopanax sp., were selected to evaluate the honey produced between April and July in South Korea. Results showed that the highest amount of DNA from each plant was detected in the corresponding flowering season. The pollens tended to accumulate in the honeycomb after the flowering season. The accumulations result in an increase in the diversity of pollen detected in honey. Additionally, DNA quantity of each plant decreased in the samples as the number of plant DNA types increased from May to July. Moreover, the authenticity of the commercial monofloral honey samples showed only cherry blossom honey was found authentic, which exhibited the expected high amount of Prunus sp. DNA. This molecular tool is expected to be useful in verifying the origin of monofloral honey and its production season.

Biomonitoring via DNA metabarcoding and light microscopy of bee pollen in rainforest transformation landscapes of Sumatra

BACKGROUND

Intense conversion of tropical forests into agricultural systems contributes to habitat loss and the decline of ecosystem functions. Plant-pollinator interactions buffer the process of forest fragmentation, ensuring gene flow across isolated patches of forests by pollen transfer. In this study, we identified the composition of pollen grains stored in pot-pollen of stingless bees, Tetragonula laeviceps, via dual-locus DNA metabarcoding (ITS2 and rbcL) and light microscopy, and compared the taxonomic coverage of pollen sampled in distinct land-use systems categorized in four levels of management intensity (forest, shrub, rubber, and oil palm) for landscape characterization.

RESULTS

Plant composition differed significantly between DNA metabarcoding and light microscopy. The overlap in the plant families identified via light microscopy and DNA metabarcoding techniques was low and ranged from 22.6 to 27.8%. Taxonomic assignments showed a dominance of pollen from bee-pollinated plants, including oil-bearing crops such as the introduced species Elaeis guineensis (Arecaceae) as one of the predominant taxa in the pollen samples across all four land-use types. Native plant families Moraceae, Euphorbiaceae, and Cannabaceae appeared in high proportion in the analyzed pollen material. One-way ANOVA (p > 0.05), PERMANOVA (R² values range from 0.14003 to 0.17684, for all tests p-value > 0.5), and NMDS (stress values ranging from 0.1515 to 0.1859) indicated a lack of differentiation between the species composition and diversity of pollen type in the four distinct land-use types, supporting the influx of pollen from adjacent areas.

CONCLUSIONS

Stingless bees collected pollen from a variety of agricultural crops, weeds, and wild plants. Plant composition detected at the family level from the pollen samples likely reflects the plant composition at the landscape level rather than the plot level. In our study, the plant diversity in pollen from colonies installed in land-use systems with distinct levels of forest transformation was highly homogeneous, reflecting a large influx of pollen transported by stingless bees through distinct land-use types. Dual-locus approach applied in metabarcoding studies and visual pollen identification showed great differences in the detection of the plant community, therefore a combination of both methods is recommended for performing biodiversity assessments via pollen identification.

Using Metabarcoding to Investigate the Strength of Plant-Pollinator Interactions From Surveys of Visits to DNA Sequences

The ongoing decline in pollinators and increasing concerns about pollination services require a better understanding of complex pollination networks, particularly their response to global climate change. While metabarcoding is increasingly used for the identification of taxa in DNA mixtures, its reliability in providing quantitative information on plant-pollinator interactions is still the subject of debate. Combining metabarcoding and microscopy, we investigated the relationships between the number and composition of sequences and the abundance and composition of pollen in insect pollen loads (IPL) and how the two are linked to insect visits. Our findings confirm that metabarcoding is more effective than microscopy in identifying plant species in IPL. For a given species, we found a strong positive relationship between the amount of pollen in IPL and the number of sequences. The relationship was stable across species even if the abundance of co-occurring species in IPL (hereafter “co-occurring pollen”) tended to reduce the sequence yield (number of sequences obtained from one pollen grain) of a given species. We also found a positive relationship between the sequence count and the frequency of visits, and between the frequency and the amounts of pollen in IPL. Our results demonstrate the reliability of metabarcoding in assessing the strength of plant-pollinator interactions and in providing a broader perspective for the analyses of plant-pollinator interactions and pollination networks.

Tracing the origin of honey products based on metagenomics and machine learning

The adulteration of honey is common. Recently, High Throughput Sequencing (HTS)-based metabarcoding method has been applied successfully to pollen/honey identification to determine floral composition that, in turn, can be used to identify the geographical origins of honeys. However, the lack of local references materials posed a serious challenge for HTS-based pollen identification methods. Here, we sampled 28 honey samples from various geographic origins without prior knowledge of local floral information and applied a machine learning method to determine geographical origins. The machine learning method uses a resilient backpropagation algorithm to train a neural network. The results showed that biological components in honey provided characteristic traits that enabled accurate geographic tracing for nearly all honey samples, confidently discriminating honeys to their geographic origin with >99% success rates, including those separated by as little as 39 km.

Next-Generation Sequencing and Its Impacts on Entomological Research in Ecology and Evolution

The advent of NGS-based methods has been profoundly transforming entomological research. Through continual development and improvement of different methods and sequencing platforms, NGS has promoted mass elucidation of partial or whole genetic materials associated with beneficial insects, pests (of agriculture, forestry and animal, and human health), and species of conservation concern, helping to unravel ecological and evolutionary mechanisms and characterizing survival, trophic interactions, and dispersal. It is shifting the scale of biodiversity and environmental analyses from individuals and biodiversity indicator species to the large-scale study of communities and ecosystems using bulk samples of species or a mixed "soup" of environmental DNA. As the NGS-based methods have become more affordable, complexity demystified, and specificity and sensitivity proven, their use in entomological research has spread widely. This article presents several examples on how NGS-based methods have been used in entomology to provide incentives to apply them when appropriate and to open our minds to the expected advances in entomology that are yet to come.

Harnessing the Power of Metabarcoding in the Ecological Interpretation of Plant-Pollinator DNA Data: Strategies and Consequences of Filtering Approaches

Although DNA metabarcoding of pollen mixtures has been increasingly used in the field of pollination biology, methodological and interpretation issues arise due to its high sensitivity. Filtering or maintaining false positives, contaminants, and rare taxa or molecular features could lead to different ecological results. Here, we reviewed how this choice has been addressed in 43 studies featuring pollen DNA metabarcoding, which highlighted a very high heterogeneity of filtering methods. We assessed how these strategies shaped pollen assemblage composition, species richness, and interaction networks. To do so, we compared four processing methods: unfiltering, filtering with a proportional 1% of sample reads, a fixed threshold of 100 reads, and the ROC approach (Receiver Operator Characteristic). The results indicated that filtering impacted species composition and reduced species richness, with ROC emerging as a conservative approach. Moreover, in contrast to unfiltered networks, filtering decreased network Connectance and Entropy, and it increased Modularity and Connectivity, indicating that using cut-off thresholds better describes interactions. Overall, unfiltering might compromise reliable ecological interpretations, unless a study targets rare species. We discuss the suitability of each filtering type, plead for justifying filtering strategies on biological or methodological bases and for developing shared approaches to make future studies more comparable.

Capabilities and limitations of using DNA metabarcoding to study plant-pollinator interactions

Many pollinator populations are experiencing declines, emphasizing the need for a better understanding of the complex relationship between bees and flowering plants. Using DNA metabarcoding to describe plant-pollinator interactions eliminates many challenges associated with traditional methods and has the potential to reveal a more comprehensive understanding of foraging behavior and pollinator life history. Here we use DNA metabarcoding of ITS2 and rbcL gene regions to identify plant species present in pollen loads of 404 bees from three habitats in eastern Oregon. Our specific objectives were to 1) determine whether plant species identified using DNA metabarcoding are consistent with plant species identified using observations, 2) compare characterizations of diet breadth derived from foraging observations to those based on plant species assignments obtained using DNA metabarcoding, and 3) compare plant species assignments produced by DNA metabarcoding using a "regional" reference database to those produced using a "local" database. At the three locations, 31-86% of foraging observations were consistent with DNA metabarcoding data, 8-50% of diet breadth characterizations based on observations differed from those based on DNA metabarcoding data, and 22-25% of plant species detected using the regional database were not known to occur in the study area in question. Plant-pollinator networks produced from DNA metabarcoding data had higher sampling completeness and significantly lower specialization than networks based on observations. Here, we examine some strengths and limitations of using DNA metabarcoding to identify plant species present in bee pollen loads, make ecological inferences about foraging behavior, and provide guidance for future research.

Pollen DNA metabarcoding identifies regional provenance and high plant diversity in Australian honey

Accurate identification of the botanical components of honey can be used to establish its geographical provenance, while also providing insights into honeybee (Apis mellifera L.) diet and foraging preferences. DNA metabarcoding has been demonstrated as a robust method to identify plant species from pollen and pollen-based products, including honey. We investigated the use of pollen metabarcoding to identify the floral sources and local foraging preferences of honeybees using 15 honey samples from six bioregions from eastern and western Australia. We used two plant metabarcoding markers, ITS2 and the trnL P6 loop. Both markers combined identified a total of 55 plant families, 67 genera, and 43 species. The trnL P6 loop marker provided significantly higher detection of taxa, detecting an average of 15.6 taxa per sample, compared to 4.6 with ITS2. Most honeys were dominated by Eucalyptus and other Myrtaceae species, with a few honeys dominated by Macadamia (Proteaceae) and Fabaceae. Metabarcoding detected the nominal primary source provided by beekeepers among the top five most abundant taxa for 85% of samples. We found that eastern and western honeys could be clearly differentiated by their floral composition, and clustered into bioregions with the trnL marker. Comparison with previous results obtained from melissopalynology shows that metabarcoding can detect similar numbers of plant families and genera, but provides significantly higher resolution at species level. Our results show that pollen DNA metabarcoding is a powerful and robust method for detecting honey provenance and examining the diet of honeybees. This is particularly relevant for hives foraging on the unique and diverse flora of the Australian continent, with the potential to be used as a novel monitoring tool for honeybee floral resources.

Honey authenticity: analytical techniques, state of the art and challenges

Honey is a high-value, globally consumed, food product featuring a high market price strictly related to its origin. Moreover, honey origin has to be clearly stated on the label, and quality schemes are prescribed based on its geographical and botanical origin. Therefore, to enhance food quality, it is of utmost importance to develop analytical methods able to accurately and precisely discriminate honey origin. In this study, an all-time scientometric evaluation of the field is provided for the first time using a structured keyword on the Scopus database. The bibliometric analysis pinpoints that the botanical origin discrimination was the most studied authenticity issue, and chromatographic methods were the most frequently used for its assessment. Based on these results, we comprehensively reviewed analytical techniques that have been used in honey authenticity studies. Analytical breakthroughs and bottlenecks on methodologies to assess honey quality parameters using separation, bioanalytical, spectroscopic, elemental and isotopic techniques are presented. Emphasis is given to authenticity markers, and the necessity to apply chemometric tools to reveal them. Altogether, honey authenticity is an ever-growing field, and more advances are expected that will further secure honey quality.

DNA traces the origin of honey by identifying plants, bacteria and fungi

The regional origin of a food product commonly affects its value. To this, DNA-based identification of tissue remains could offer fine resolution. For honey, this would allow the usage of not only pollen but all plant tissue, and also that of microbes in the product, for discerning the origin. Here we examined how plant, bacterial and fungal taxa identified by DNA metabarcoding and metagenomics differentiate between honey samples from three neighbouring countries. To establish how the taxonomic contents of honey reflect the country of origin, we used joint species distribution modelling. At the lowest taxonomic level by metabarcoding, with operational taxonomic units, the country of origin explained the majority of variation in the data (70-79%), with plant and fungal gene regions providing the clearest distinction between countries. At the taxonomic level of genera, plants provided the most separation between countries with both metabarcoding and metagenomics. The DNA-based methods distinguish the countries more than the morphological pollen identification and the removal of pollen has only a minor effect on taxonomic recovery by DNA. As we find good resolution among honeys from regions with similar biota, DNA-based methods hold great promise for resolving honey origins among more different regions.

Testing the effect of pollen exine rupture on metabarcoding with Illumina sequencing

Pollen metabarcoding has received much attention recently for its potential to increase taxonomic resolution of the identifications of pollen grains necessary for various public health, ecological and environmental inquiry. However, methodologies implemented are widely varied across studies confounding comparisons and casting uncertainty on the reliability of results. In this study, we investigated part of the methodology, the effects of level of exine rupture and lysis incubation time, on the performance of DNA extraction and Illumina sequencing. We examined 15 species of plants from 12 families with pollen that varies in size, shape, and aperture number to evaluate effort necessary for exine rupture. Then created mock communities of 14 of the species from DNA extractions at 4 levels of exine rupture (0, 33, 67, and 100%) and two levels of increased lysis incubation time without exine rupture (2 or 24 hours). Quantities of these DNA extractions displayed a positive correlation between increased rupture and DNA yield, however increasing time of lysis incubation was associated with decreased DNA yield. Illumina sequencing was performed with these artificial community treatments with three common plant DNA barcode regions (rbcL, ITS1, ITS2) with two different primer pairings for ITS2 and rbcL. We found decreased performance in treatments with 0% or 100% exine rupture compared to 33% and 67% rupture, based on deviation from expected proportions and species retrieval, and increased lysis incubation was found to be detrimental to results.

Floral hosts of leaf-cutter bees (Megachilidae) in a biodiversity hotspot revealed by pollen DNA metabarcoding of historic specimens

South Africa is a megadiverse country with three globally recognised biodiversity hotspots within its borders. Bees in particular show high diversity and endemism in the western part of the country. Not much is currently known about the floral host preferences of indigenous bees in South Africa, with data only available from observational studies. Pollen metabarcoding provides provenance information by utilising DNA analyses instead of floral visitation and traditional microscopic identification to identify pollinator food plants, which can be time consuming and imprecise. In this study, we sampled pollen from leaf-cutter bees (Megachilidae) specimens maintained in a historic insect collection (National Collection of Insects, South Africa) that were originally collected from two florally important areas in South Africa (Succulent Karoo and Savanna) and used metabarcoding to determine pollen provenance. We also sampled pollen from leafcutter bee species with wider distributions, that extend across many different biomes, to determine if these 'generalist' species show relaxed floral host specificity in some biomes. Metabarcoding involved sequencing of the nuclear internal transcribed spacer 2 (ITS2) region. Amplicons were compared to a sequence reference database to assign taxonomic classifications to family level. Sequence reads were also clustered to OTUs based on 97% sequence similarity to estimate numbers of plant species visited. We found no significant difference in the mean number of plant taxa visited in the Succulent Karoo and Savanna regions, but the widespread group visited significantly more floral hosts. Bees from the widespread group were also characterised by a significantly different composition in pollen assemblage. The time since specimens were collected did not have an effect on the mean number of taxa visited by any of the bee species studied. This study highlights national history collections as valuable sources of temporal and spatial biodiversity data.

Employing DNA metabarcoding to determine the geographical origin of honey

Unfavourable climatic conditions force Iranian beekeepers to translocate over large distances in the course of the year. However, irrespective of the main place of production, the honey is always labeled with the name of the beekeepers' hometown, which leads consequently to mislabeled products. The present study investigates the capability of DNA metabarcoding to locate the geographical origin of honey. The molecular markers (ITS2 and rbcL) allowed identification of 926 plant species in studied samples. A comprehensive review of floristic reference books specified 34 key species that could be used to successfully determine the geographical origin in 91.4% of samples. These key species were usually present in honey with tiny amounts and thus, conventional palynology might not be able to detect them. The present investigation indicates that although ITS2 is able to detect more species than rbcL, utilizing a combination of both markers provides more robust evidence of geographical origin.

Comparative and Functional Screening of Three Species Traditionally used as Antidepressants: Valeriana officinalis L., Valeriana jatamansi Jones ex Roxb. and Nardostachys jatamansi (D.Don) DC

The essential oils (EOs) of three Caprifoliaceae species, the Eurasiatic Valeriana officinalis (Vo), the Himalayan Valeriana jatamansi (Vj) and Nardostachys jatamansi (Nj), are traditionally used to treat neurological disorders. Roots/rhizomes micromorphology, DNA barcoding and EOs phytochemical characterization were carried out, while biological effects on the nervous system were assessed by acetylcholinesterase (AChE) inhibitory activity and microelectrode arrays (MEA). Nj showed the highest inhibitory activity on AChE (IC₅₀ 67.15 μg/mL) followed by Vo (IC₅₀ 127.30 μg/mL) and Vj (IC₅₀ 246.84 μg/mL). MEA analyses on rat cortical neurons, carried out by recording mean firing rate (MFR) and mean bursting rate (MBR), revealed stronger inhibition by Nj (IC₅₀ 18.8 and 11.1 μg/mL) and Vo (16.5 and 22.5 μg/mL), compared with Vj (68.5 and 89.3 μg/mL). These results could be related to different EO compositions, since sesquiterpenes and monoterpenes significantly contribute to the observed effects, but the presence of oxygenated compounds such as aldehydes and ketones is a discriminating factor in determining the order of potency. Our multidisciplinary approach represents an important tool to avoid the adulteration of herbal drugs and permits the evaluation of the effectiveness of EOs that could be used for a wide range of therapeutic applications.

Modern Methods for Assessing the Quality of Bee Honey and Botanical Origin Identification

This paper is a summary of the latest literature on methods for assessing quality of natural bee honey. The publication briefly characterizes methods recommended by the International Honey Commission, published in 2009, as well as newer methods published in the last 10 years. Modern methods of assessing honey quality focus mainly on analyzing markers of individual varieties and classifying them into varieties, using, among others, near infrared spectroscopy techniques (NIR), potentiometric tongue, electronic nose, nuclear magnetic resonance (NMR), zymography, polymerase chain reaction (PCR), DNA metabarcoding, and chemometric techniques including partial least squares (PLS), principal component analysis (PCA) and artificial neural networks (ANN). At the same time, effective techniques for analyzing adulteration, sugar, and water content, hydroxymethylfurfural (HMF), polyphenol content, and diastase activity are being sought. Modern techniques enable the results of honey quality testing to be obtained in a shorter time, using the principles of green chemistry, allowing, at the same time, for high precision and accuracy of determinations. These methods are constantly modified, so that the honey that is on sale is a product of high quality. Prospects for devising methods of honey quality assessment include the development of a fast and accurate alternative to the melissopalynological method as well as quick tests to detect adulteration.

Microbial metabarcoding highlights different bacterial and fungal populations in honey samples from local beekeepers and market in north-eastern Italy

Due to its chemical properties, honey does not foster the growth of microorganisms, however it may contain a rich microbial community, including viable, stressed, and not viable microbes. In order to characterize honey microbiota focusing on the difference between products from beekeepers and large retail in the present study a culture-independent approach based on DNA metabarcoding was applied. Honey samples were collected from Local Beekeepers (LB) and Market sales (M) during four years with the aim to investigate the microbiological quality in the honey market. Extraction and amplification of DNA from honey samples showed reduced efficiency with increasing age of honey, with the loss of 50-80% of samples four years old (2014). For this reason, only samples of similar age were compared and the analysis of microbial communities focused on year 2017, for a total of 75 samples. Differences in alpha and beta-diversity were evidenced comparing microbial communities between LB and M samples. In particular, contaminant bacteria dominated the microbiota in M samples while LB samples were enriched in Lactic Acid Bacteria (LAB) that cannot be isolated with culture-dependent approaches.

Detection and quantification of cashew in commercial tea products using High Resolution Melting (HRM) analysis

Tea, a popular aromatic infusion and food supplement, prepared from Camellia sinensis (L.) Kuntze leaves, is often subjected to adulteration with various undeclared inorganic and plant-derived materials. Cashew (Anacardium occidentale L.) nut husk is one of the most common plant tea adulterants. To date, there are limited DNA-based technologies for tea authentication and quantitative detection of adulterants. Herein, we used a universal plant DNA barcoding marker coupled with High Resolution Melting (Bar-HRM) analysis to authenticate tea products from cashew ground nut. Additionally, cashew-specific markers coupled with HRM technology were used to detect and quantify adulteration of tea with cashew DNA. This methodology can reliably detect admixtures as low as 1% v/v cashew in commercial tea products. Overall, our results demonstrate that the HRM technology is a strong molecular approach in tea authentication, capable of detecting very low adulterations in DNA admixtures. PRACTICAL APPLICATION: In this study, we established the use of high-resolution DNA-based technologies for the detection of cashew adulteration in tea, even in very low quantities. The technology could be applied to a greater range of plant-based tea adulterants. This work is expected to facilitate the traceability and authenticity of tea products and form the basis for the development of strategies against fraudulent practices.

DNA barcoding coupled with high-resolution melting analysis for nut species and walnut milk beverage authentication

BACKGROUND

Walnut (Juglans regia L.) is one of the most widely cultivated nuts. Walnut milk beverage is very popular in China due to its nutritional value. However, adulterated walnut milk ingredients have been detected in the Chinese market. Peanut and soybean are sold at much lower prices than walnut and are reported to be commonly used for adulteration in the industrial chain of walnut milk production. The purpose of this study is therefore to develop an accurate and efficient method for detecting the authenticity of the raw materials used in walnut milk beverage.

RESULTS

DNA barcoding and high-resolution melting (HRM) analyses were used to identify common adulterated raw ingredients such as peanut and soybean in commercial walnut milk beverage samples. The chloroplast psbA-trnH gene was used for sequencing, and HRM analysis was performed. We also prepared experimental mixtures, in the laboratory, with different quantities of walnut, peanut, and soybean. High-resolution melting analysis of the experimental mixtures clearly distinguished all of them. The results revealed that most of the walnut milk beverage samples fell in the same cluster of walnut species. Several samples fell in the peanut cluster, confirming that they were adulterated products.

CONCLUSION

The results revealed that HRM analysis based on the psbA-trnH barcode sequence can be used to identify raw ingredients in walnut milk beverages. © 2020 Society of Chemical Industry.

Experimental quantification of pollen with DNA metabarcoding using ITS1 and trnL

Although the use of metabarcoding to identify taxa in DNA mixtures is widely approved, its reliability in quantifying taxon abundance is still the subject of debate. In this study we investigated the relationships between the amount of pollen grains in mock solutions and the abundance of high-throughput sequence reads and how the relationship was affected by the pollen counting methodology, the number of PCR cycles, the type of markers and plant species whose pollen grains have different characteristics. We found a significant positive relationship between the number of DNA sequences and the number of pollen grains in the mock solutions. However, better relationships were obtained with light microscopy as a pollen grain counting method compared with flow cytometry, with the chloroplastic trnL marker compared with ribosomal ITS1 and with 30 when compared with 25 or 35 PCR cycles. We provide a list of recommendations to improve pollen quantification.

Heavy metal tolerance of orchid populations growing on abandoned mine tailings: A case study in Sardinia Island (Italy)

Understanding how environmental pollutants influence plant occurrence, growth, and development is key for effective management plans and potential bioremediation. Rare plants, such as orchids, may occur in modified habitats and on soils containing heavy metals, yet their ecological and physiological responses to heavy metals is poorly understood. We investigated the influence of heavy metal pollution on orchid growth rates and interactions with soil fungal mutualists by comparing a large population of the orchid Epipactis helleborine (L.) Crantz subsp. tremolsii (Pau) E. Klein that grows on mine tailings in south-west Sardinia (Italy) with a population that grows on non-contaminated soils in central Sardinia. Soils of the contaminated site had high levels of heavy metals and low organic matter and nutritive elements content. We performed a morphological analysis on twenty individuals that have been subjected to measurement of bioaccumulation and translocation of heavy metals. Fungi associated with the roots of plants from the contaminated and uncontaminated site were grown and identified by DNA barcoding approach. Plants from the contaminated site were smaller than the ones growing in the uncontaminated site and were found to be able to tolerate heavy metals from the soil and to accumulate and translocate them into their organs. Fungi belonging to the genus Ilyonectria (Ascomycota) were found both in contaminated and uncontaminated sites, while an unidentified fungus was isolated from roots in the contaminated site only. These results are discussed in terms of orchids' tolerance to heavy metals and its physiological and ecological mechanisms. The role of contaminated habitats in harbouring orchids and peculiar taxa is also discussed.

DNA barcoding detects floral origin of Indian honey samples

The unique medicinal and nutritional properties of honey are determined by its chemical composition. To evaluate the quality of honey, it is essential to study the surrounding vegetation where honeybees forage. In this study we used conventional melissopalynological and DNA barcoding techniques to determine the floral source of honey samples collected from different districts of the state of Mizoram, India. Pollen grains were isolated and genomic DNA was extracted from the honey samples. PCR amplification was carried out using universal barcode candidates ITS2 and rbcL to identify the plant species. Furthermore, TA cloning was carried out to screen the PCR amplicon libraries to identify the presence of multiple plant species. Results from both the melissopalynological and DNA barcoding analyses identified almost exactly the same 22 species, suggesting that both methods are suitable for analysis. However, DNA barcoding is easier and widely practiced. Hence, it can be concluded that DNA barcoding is a useful tool in determining the medicinal and commercial value of honey.

Review of Recent DNA-Based Methods for Main Food-Authentication Topics

Adulteration and mislabeling of food products and the commercial fraud derived, either intentionally or not, is a global source of economic fraud to consumers but also to all stakeholders involved in food production and distribution. Legislation has been enforced all over the world aimed at guaranteeing the authenticity of the food products all along the distribution chain, thereby avoiding food fraud and adulteration. Accordingly, there is a growing need for new analytical methods able to verify that all the ingredients included in a foodstuff match the qualities claimed by the manufacturer or distributor. In this sense, the improved performance of most recent DNA-based tools in term of sensitivity, multiplexing ability, high-throughput, and relatively low-cost give them a game-changing role in food-authenticity-related topics. Here, we provide a thorough and updated vision on the recently reported approaches that are applying these DNA-based tools to assess the authenticity of food components and products.

Food Tracking Perspective: DNA Metabarcoding to Identify Plant Composition in Complex and Processed Food Products

One of the main goals of the quality control evaluation is to identify contaminants in raw material, or contamination after a food is processed and before it is placed on the market. During the treatment processes, contamination, both accidental and economically motivated, can generate incongruence between declared and real composition. In our study, we evaluated if DNA metabarcoding is a suitable tool for unveiling the composition of processed food, when it contains small trace amounts. We tested this method on different types of commercial plant products by using tnrL marker and we applied amplicon-based high-throughput sequencing techniques to identify plant components in different food products. Our results showed that DNA metabarcoding can be an effective approach for food traceability in different type of processed food. Indeed, the vast majority of our samples, we identified the species composition as the labels reported. Although some critical issues still exist, mostly deriving from the starting composition (i.e., variable complexity in taxa composition) of the sample itself and the different processing level (i.e., high or low DNA degradation), our data confirmed the potential of the DNA metabarcoding approach also in quantitative analyses for food composition quality control.

Plant-pollinator interactions over time: Pollen metabarcoding from bees in a historic collection

Pollination is a key component in agricultural food production and ecosystem maintenance, with plant-pollinator interactions an important research theme in ecological and evolutionary studies. Natural history collections provide unique access to samples collected at different spatial and temporal scales. Identification of the plant origins of pollen trapped on the bodies of pollinators in these collections provides insight into historic plant communities and pollinators' preferred floral taxa. In this study, pollen was sampled from Megachile venusta Smith bees from the National Collection of Insects, South Africa, spanning 93 years. Three barcode regions, the internal transcribed spacer 1 and 2 (ITS1 and ITS2) and ribulose-1,5-biphosphate carboxylase (rbcL), were sequenced from mixed pollen samples using a next-generation sequencing approach (MiSeq, Illumina). Sequenced reads were compared to sequence reference databases that were generated by extracting sequence and taxonomic data from GenBank. ITS1 and ITS2 were amplified successfully across all (or most) samples, while rbcL performed inconsistently. Age of sample had no impact on sequencing success. Plant classification was more informative using ITS2 than ITS1 barcode data. This study also highlights the need for comprehensive reference databases as limited local plant sequence representation in reference databases resulted in higher-level taxon classifications being more confidently interpreted. The results showed that small, insect-carried pollen samples from historic bee specimens collected from as early as 1914 can be used to obtain pollen metabarcodes. DNA metabarcoding of mixed origin pollen samples provided a faster, more accurate method of determining pollen provenance, without the need for expert palynologists. The use of historic collections to sample pollen directly from pollinators provided additional value to these collections. Sampling pollen from historic collections can potentially provide the spatial and temporal scales for investigations into changes in plant community structure or pollinator floral choice in the face of global climate change.

A next generation sequencing approach for targeted Varroa destructor (Acari: Varroidae) mitochondrial DNA analysis based on honey derived environmental DNA

Honey contains DNA from many different organisms that are part of hive micro-environmental niches and honey bee pathospheres. In this study, we recovered and sequenced mite mitochondrial DNA (mtDNA) from honey from different locations around the world (Europe, Asia, Africa, North and South America). DNA extracted from 17 honey samples was amplified with eight primer pairs targeting three mite mtDNA genes, obtaining 88 amplicons that were sequenced with an Ion Torrent sequencing platform. A bioinformatic pipeline compared produced reads with Varroa spp. mtDNA sequence entries available in GenBank and assigned them to different mitotypes. In all honey samples, the highest percentage of reads was attributed to the K1 lineage, including a few variants derived from it, in addition to J1 reads observed in the two South American samples and C1-1 reads obtained from the Chinese honey. This study opens new possibilities to analyse mite lineages and variants and monitor their geographical and temporal distribution, simplifying surveillance against this damaging honey bee parasite.

Pollen metabarcoding as a tool for tracking long-distance insect migrations

Insects account for a large portion of Earth's biodiversity and are key players for ecosystems, notably as pollinators. While insect migration is suspected to represent a natural phenomenon of major importance, remarkably little is known about it, except for a few flagship species. The reason for this situation is mainly due to technical limitations in the study of insect movement. Here, we propose using metabarcoding of pollen carried by insects as a method for tracking their migrations. We developed a flexible and simple protocol allowing efficient multiplexing and not requiring DNA extraction, one of the most time-consuming part of metabarcoding protocols, and apply this method to the study of the long-distance migration of the butterfly Vanessa cardui, an emerging model for insect migration. We collected 47 butterfly samples along the Mediterranean coast of Spain in spring and performed metabarcoding of pollen collected from their bodies to test for potential arrivals from the African continent. In total, we detected 157 plant species from 23 orders, most of which (82.8%) were insect-pollinated. Taxa present in Africa-Arabia represented 73.2% of our data set, and 19.1% were endemic to this region, strongly supporting the hypothesis that migratory butterflies colonize southern Europe from Africa in spring. Moreover, our data suggest that a northwards trans-Saharan migration in spring is plausible for early arrivals (February) into Europe, as shown by the presence of Saharan floristic elements. Our results demonstrate the possibility of regular insect-mediated transcontinental pollination, with potential implications for ecosystem functioning, agriculture and plant phylogeography.

Flower preferences and pollen transport networks for cavity-nesting solitary bees: Implications for the design of agri-environment schemes

Floral foraging resources are valuable for pollinator conservation on farmland, and their provision is encouraged by agri-environment schemes in many countries. Across Europe, wildflower seed mixtures are widely sown on farmland to encourage pollinators, but the extent to which key pollinator groups such as solitary bees exploit and benefit from these resources is unclear. We used high-throughput sequencing of 164 pollen samples extracted from the brood cells of six common cavity-nesting solitary bee species (Osmia bicornis, Osmia caerulescens, Megachile versicolor, Megachile ligniseca, Megachile centuncularis and Hylaeus confusus) which are widely distributed across the UK and Europe. We documented their pollen use across 19 farms in southern England, UK, revealing their forage plants and examining the structure of their pollen transport networks. Of the 32 plant species included currently in sown wildflower mixes, 15 were recorded as present within close foraging range of the bees on the study farms, but only Ranunculus acris L. was identified within the pollen samples. Rosa canina L. was the most commonly found of the 23 plant species identified in the pollen samples, suggesting that, in addition to providing a nesting resource for Megachile leafcutter bees, it may be an important forage plant for these species. Higher levels of connectance and nestedness were characteristic of pollen transport networks on farms with abundant floral resources, which may increase resilience to species loss. Our data suggest that plant species promoted currently by agri-environment schemes are not optimal for solitary bee foraging. If a diverse community of pollinators is to be supported on UK and European farmland, additional species such as R. canina should be encouraged to meet the foraging requirements of solitary bees.

Entomological signatures in honey: an environmental DNA metabarcoding approach can disclose information on plant-sucking insects in agricultural and forest landscapes

Honeydew produced from the excretion of plant-sucking insects (order Hemiptera) is a carbohydrate-rich material that is foraged by honey bees to integrate their diets. In this study, we used DNA extracted from honey as a source of environmental DNA to disclose its entomological signature determined by honeydew producing Hemiptera that was recovered not only from honeydew honey but also from blossom honey. We designed PCR primers that amplified a fragment of mitochondrial cytochrome c oxidase subunit 1 (COI) gene of Hemiptera species using DNA isolated from unifloral, polyfloral and honeydew honeys. Ion Torrent next generation sequencing metabarcoding data analysis assigned Hemiptera species using a customized bioinformatic pipeline. The forest honeydew honeys reported the presence of high abundance of Cinara pectinatae DNA, confirming their silver fir forest origin. In all other honeys, most of the sequenced reads were from the planthopper Metcalfa pruinosa for which it was possible to evaluate the frequency of different mitotypes. Aphids of other species were identified from honeys of different geographical and botanical origins. This unique entomological signature derived by environmental DNA contained in honey opens new applications for honey authentication and to disclose and monitor the ecology of plant-sucking insects in agricultural and forest landscapes.

Generalisation and specialisation in hoverfly (Syrphidae) grassland pollen transport networks revealed by DNA metabarcoding

Pollination by insects is a key ecosystem service and important to wider ecosystem function. Most species-level pollination networks studied have a generalised structure, with plants having several potential pollinators, and pollinators in turn visiting a number of different plant species. This is in apparent contrast to a plant's need for efficient conspecific pollen transfer. The aim of this study was to investigate the structure of pollen transport networks at three levels of biological hierarchy: community, species and individual. We did this using hoverflies in the genus Eristalis, a key group of non-Hymenopteran pollinators. We constructed pollen transport networks using DNA metabarcoding to identify pollen. We captured hoverflies in conservation grasslands in west Wales, UK, removed external pollen loads, sequenced the pollen DNA on the Illumina MiSeq platform using the standard plant barcode rbcL, and matched sequences using a pre-existing plant DNA barcode reference library. We found that Eristalis hoverflies transport pollen from 65 plant taxa, more than previously appreciated. Networks were generalised at the site and species level, suggesting some degree of functional redundancy, and were more generalised in late summer compared to early summer. In contrast, pollen transport at the individual level showed some degree of specialisation. Hoverflies defined as "single-plant visitors" varied from 40% of those captured in early summer to 24% in late summer. Individual hoverflies became more generalised in late summer, possibly in response to an increase in floral resources. Rubus fruticosus agg. and Succisa pratensis were key plant species for hoverflies at our sites Our results contribute to resolving the apparent paradox of how generalised pollinator networks can provide efficient pollination to plant species. Generalised hoverfly pollen transport networks may result from a varied range of short-term specialised feeding bouts by individual insects. The generalisation and functional redundancy of Eristalis pollen transport networks may increase the stability of the pollination service they deliver.